class_docstr: A context for controlling metrics recording when async checkpoint is used.
    
class_docstr_tok: ["A","context","for","controlling","metrics","recording","when","async","checkpoint","is","used","."]
code: def enter_async_metrics_context(self):
      self._in_async_metrics_context = True
  
file_path: tensorflow/tensorflow/python/checkpoint/checkpoint_context.py
imports: import contextlib
  import threading
label_desc: Use image node_id 2 for calling the AsyncMetricsContext obj's underlying member method code with example usage: obj.enter_async_metrics_context() without return types